Department of Chemistry, Saint Louis University, Saint Louis, Missouri 63103, USA.
RNA. 2022 Jun;28(6):832-841. doi: 10.1261/rna.078915.121. Epub 2022 Mar 22.
RNA folding is hierarchical; therefore, predicting RNA secondary structure from sequence is an intermediate step in predicting tertiary structure. Secondary structure prediction is based on a nearest neighbor model using free energy minimization. To improve secondary structure prediction, all types of naturally occurring secondary structure motifs need to be thermodynamically characterized. However, not all secondary structure motifs are well characterized. Pentaloops, the second most abundant hairpin size, is one such uncharacterized motif. In fact, the current thermodynamic model used to predict the stability of pentaloops was derived from a small data set of pentaloops and from data for other hairpins of different sizes. Here, the most commonly occurring pentaloops were identified and optically melted. New experimental data for 22 pentaloop sequences were combined with previously published data for nine pentaloop sequences. Using linear regression, a pentaloop-specific model was derived. This new model is simpler and more accurate than the current model. The new experimental data and improved model can be incorporated into software that is used to predict RNA secondary structure from sequence.
RNA 折叠具有层次性；因此，从序列预测 RNA 二级结构是预测三级结构的中间步骤。二级结构预测是基于自由能最小化的最近邻模型进行的。为了提高二级结构预测的准确性，需要对所有类型的天然存在的二级结构基序进行热力学特征描述。然而，并非所有的二级结构基序都得到了很好的描述。五聚体环是第二丰富的发夹大小，就是这样一个未被充分描述的基序。事实上，目前用于预测五聚体环稳定性的热力学模型是从一个五聚体环的小数据集和其他不同大小发夹的数据集推导出来的。在这里，确定了最常见的五聚体环，并对其进行了光学熔化。将 22 个五聚体环序列的新实验数据与之前发表的 9 个五聚体环序列的数据相结合。使用线性回归，推导出了一个专门针对五聚体环的模型。这个新模型比现有的模型更简单、更准确。新的实验数据和改进的模型可以被整合到用于从序列预测 RNA 二级结构的软件中。
